Interconnected Automation Systems (IAS)
At the Chair of Interconnected Automation Systems (IAS) at the University of Siegen, we drive basic and applied research on design automation of software and hardware to improve the reliability, efficiency and sustainability of modern cyber-physical infrastructures - from industrial and mechatronic systems to energy conversion applications and electrical power systems.
Mission statement
We conduct rigorous, open and responsible research on interconnected automation systems and translate sound modeling, control and data-driven methods into trustworthy technologies that increase safety and reliability, reduce energy plus resource consumption and strengthen resilient infrastructures for the benefit of society. In teaching, we qualify engineers and researchers to combine a physical-analytical understanding of systems with computer-aided and data-oriented tools so that they can actively shape future generations of automation and energy systems.
Chair's head
Research profile
We research networked cyber-physical systems in industrial automation and mechatronics as well as in electrified energy technologies. Central fields of application are electric drives, power electronic converters, energy storage systems and charging infrastructures as well as networked electrical energy systems such as microgrids - with the aim of enabling more reliable, efficient and resilient operation under real operating conditions.
Our work covers the entire innovation chain from basic research to industrial transfer. A particular focus is on translating theoretical concepts into practical proof-of-concepts, supported by rapid software and hardware prototyping. Experimental validation, including targeted measurement campaigns on relevant test benches, is an integral part of our research process.
Open science is a cornerstone of our research practice. We publish open source software, reproducible workflows and other open resources to enable transparent evaluation, benchmarking and rapid knowledge transfer for students, researchers and industry partners. Our open source contributions can be found on GitHub: https://github.com/IAS-Uni-Siegen
Focus areas
- Optimal control methods (e.g., reinforcement learning, differential predictive control)
- Hardware design, optimization and testing of power electronic converters (component and system level)
- Hybrid modeling and system identification (combination of expert and data knowledge)
- Condition monitoring, diagnostics and digital twins (e.g. using fault and anomaly detection)
- State and parameter estimation (observer, co-estimator)
- Software-driven automation (reproducible design toolchains, verification and benchmarking)
Latest publications
Influence of Initialisation Parameter in Extended Kalman Filter on State of Charge Estimation
Influence of Initialisation Parameter in Extended Kalman Filter on State of Charge Estimation
Protocol for conducting advanced cyclic tests in lithium-ion batteries to estimate capacity fade
Protocol for conducting advanced cyclic tests in lithium-ion batteries to estimate capacity fade
Using a High-frequency Switching Power Converter for Online Electrochemical Impedance Spectroscopy on an Electrolyser System
Using a High-frequency Switching Power Converter for Online Electrochemical Impedance Spectroscopy on an Electrolyser System
Distributed control of partial differential equations using convolutional reinforcement learning
Distributed control of partial differential equations using convolutional reinforcement learning
Cloud-based Battery Test Bed Development for Life Cycle and Performance Evaluation for Electric Vehicle Applications
Cloud-based Battery Test Bed Development for Life Cycle and Performance Evaluation for Electric Vehicle Applications
Operational Insights into a 4 MVA Microgrid Laboratory for Decentralized Power Electronic Applications
Operational Insights into a 4 MVA Microgrid Laboratory for Decentralized Power Electronic Applications
Design of a Current Control System for Generating Various Current Forms
Design of a Current Control System for Generating Various Current Forms
Pre-Processing Measurement Data for Computing Internal DC Resistance with Anomaly Detection Techniques
Pre-Processing Measurement Data for Computing Internal DC Resistance with Anomaly Detection Techniques
The Impact of Relaxation Time on Cell Degradation across the Life Cycle under diverse operating temperatures
The Impact of Relaxation Time on Cell Degradation across the Life Cycle under diverse operating temperatures
Insights and Challenges of Co-Simulation-Based Optimal Pulse Pattern Evaluation for Electric Drives
Insights and Challenges of Co-Simulation-Based Optimal Pulse Pattern Evaluation for Electric Drives
Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches
Hybrid control of interconnected power converters using both expert-driven droop and data-driven reinforcement learning approaches
Design and Development of AC Impedance Measurement Test Circuit for Lithium-ion Cells
Design and Development of AC Impedance Measurement Test Circuit for Lithium-ion Cells
Pagination
- First page
- Previous page
- …
- 4
- 5
- 6
- …
- Next page
- Last page
Opening hours secretariat
Opening hours
Postal address
University of Siegen
Chair of Interconnected Automation Systems (IAS)
Hölderlinstraße 3
57076 Siegen
Visitor address
University of Siegen
Chair of Interconnected Automation Systems (IAS)
H-A Level 4
Room: H-A 4106/3
Hölderlinstraße 3
57076 Siegen
Secretariat
Secretary: Lada Lübke
Phone: +49 (0)271 / 740-3305
Fax: +49 (0)271 / 740-13305
Room: H-A 4106/3
E-Mail: IAS-office@eti.uni-siegen.de